Competency Framework Development for Genomics Nurse Educators
Bibliographic record
Abstract
BACKGROUND: As genomics becomes increasingly integral to health care, enhancing nurse educators' competence in teaching genomics is vital for sustaining nursing's role in precision health. PROBLEM: Many nurses lack confidence in applying genomics in practice, highlighting the need for improved genomics nursing education. APPROACH: The International Society for Nurses in Genetics convened a steering committee to develop a competency framework defining the role of Genomics Nurse Educators. We applied the Six-Step Model for Competency Framework Development in Healthcare Professions, drawing on targeted literature review and international stakeholder input to draft the framework. OUTCOMES: The resulting framework includes 3 domains and 7 competency areas defining the knowledge, expertise, and leadership required for Genomics Nurse Educators. CONCLUSIONS: The framework advances genomic nursing education globally, transitioning it from an emerging to an evolving specialty; provides a structured pathway for faculty development, supports integration of genomics into curricula, and promotes education of genomics-informed nurses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".